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Publication search results
found 54 matches
- 2023
- Mathieu Even, Scott Pesme, Suriya Gunasekar, Nicolas Flammarion:
(S)GD over Diagonal Linear Networks: Implicit bias, Large Stepsizes and Edge of Stability. NeurIPS 2023 - Mathieu Even, Scott Pesme, Suriya Gunasekar, Nicolas Flammarion:
(S)GD over Diagonal Linear Networks: Implicit Regularisation, Large Stepsizes and Edge of Stability. CoRR abs/2302.08982 (2023) - Suriya Gunasekar, Yi Zhang, Jyoti Aneja, Caio César Teodoro Mendes, Allie Del Giorno, Sivakanth Gopi, Mojan Javaheripi, Piero Kauffmann, Gustavo de Rosa, Olli Saarikivi, Adil Salim, Shital Shah, Harkirat Singh Behl, Xin Wang, Sébastien Bubeck, Ronen Eldan, Adam Tauman Kalai, Yin Tat Lee, Yuanzhi Li:
Textbooks Are All You Need. CoRR abs/2306.11644 (2023) - Yuanzhi Li, Sébastien Bubeck, Ronen Eldan, Allie Del Giorno, Suriya Gunasekar, Yin Tat Lee:
Textbooks Are All You Need II: phi-1.5 technical report. CoRR abs/2309.05463 (2023) - Mert Yüksekgönül, Varun Chandrasekaran, Erik Jones, Suriya Gunasekar, Ranjita Naik, Hamid Palangi, Ece Kamar, Besmira Nushi:
Attention Satisfies: A Constraint-Satisfaction Lens on Factual Errors of Language Models. CoRR abs/2309.15098 (2023) - Marah I Abdin, Suriya Gunasekar, Varun Chandrasekaran, Jerry Li, Mert Yüksekgönül, Rahee Ghosh Peshawaria, Ranjita Naik, Besmira Nushi:
KITAB: Evaluating LLMs on Constraint Satisfaction for Information Retrieval. CoRR abs/2310.15511 (2023) - 2022
- Meena Jagadeesan, Ilya P. Razenshteyn, Suriya Gunasekar:
Inductive Bias of Multi-Channel Linear Convolutional Networks with Bounded Weight Norm. COLT 2022: 2276-2325 - Yunhao Ge, Harkirat S. Behl, Jiashu Xu, Suriya Gunasekar, Neel Joshi, Yale Song, Xin Wang, Laurent Itti, Vibhav Vineet:
Neural-Sim: Learning to Generate Training Data with NeRF. ECCV (23) 2022: 477-493 - Ruoqi Shen, Sébastien Bubeck, Suriya Gunasekar:
Data Augmentation as Feature Manipulation. ICML 2022: 19773-19808 - Ruoqi Shen, Sébastien Bubeck, Suriya Gunasekar:
Data Augmentation as Feature Manipulation: a story of desert cows and grass cows. CoRR abs/2203.01572 (2022) - Yi Zhang, Arturs Backurs, Sébastien Bubeck, Ronen Eldan, Suriya Gunasekar, Tal Wagner:
Unveiling Transformers with LEGO: a synthetic reasoning task. CoRR abs/2206.04301 (2022) - Suriya Gunasekar:
Generalization to translation shifts: a study in architectures and augmentations. CoRR abs/2207.02349 (2022) - Yunhao Ge, Harkirat S. Behl, Jiashu Xu, Suriya Gunasekar, Neel Joshi, Yale Song, Xin Wang, Laurent Itti, Vibhav Vineet:
Neural-Sim: Learning to Generate Training Data with NeRF. CoRR abs/2207.11368 (2022) - Ananya Kumar, Ruoqi Shen, Sébastien Bubeck, Suriya Gunasekar:
How to Fine-Tune Vision Models with SGD. CoRR abs/2211.09359 (2022) - 2021
- Suriya Gunasekar, Blake E. Woodworth, Nathan Srebro:
Mirrorless Mirror Descent: A Natural Derivation of Mirror Descent. AISTATS 2021: 2305-2313 - Meena Jagadeesan, Ilya P. Razenshteyn, Suriya Gunasekar:
Inductive Bias of Multi-Channel Linear Convolutional Networks with Bounded Weight Norm. CoRR abs/2102.12238 (2021) - 2020
- Blake E. Woodworth, Suriya Gunasekar, Jason D. Lee, Edward Moroshko, Pedro Savarese, Itay Golan, Daniel Soudry, Nathan Srebro:
Kernel and Rich Regimes in Overparametrized Models. COLT 2020: 3635-3673 - Yiding Jiang, Parth Natekar, Manik Sharma, Sumukh K. Aithal, Dhruva Kashyap, Natarajan Subramanyam, Carlos Lassance, Daniel M. Roy, Gintare Karolina Dziugaite, Suriya Gunasekar, Isabelle Guyon, Pierre Foret, Scott Yak, Hossein Mobahi, Behnam Neyshabur, Samy Bengio:
Methods and Analysis of The First Competition in Predicting Generalization of Deep Learning. NeurIPS (Competition and Demos) 2020: 170-190 - Edward Moroshko, Blake E. Woodworth, Suriya Gunasekar, Jason D. Lee, Nati Srebro, Daniel Soudry:
Implicit Bias in Deep Linear Classification: Initialization Scale vs Training Accuracy. NeurIPS 2020 - Xiaoxia Wu, Edgar Dobriban, Tongzheng Ren, Shanshan Wu, Zhiyuan Li, Suriya Gunasekar, Rachel A. Ward, Qiang Liu:
Implicit Regularization and Convergence for Weight Normalization. NeurIPS 2020 - Blake E. Woodworth, Suriya Gunasekar, Jason D. Lee, Edward Moroshko, Pedro Savarese, Itay Golan, Daniel Soudry, Nathan Srebro:
Kernel and Rich Regimes in Overparametrized Models. CoRR abs/2002.09277 (2020) - Suriya Gunasekar, Blake E. Woodworth, Nathan Srebro:
Mirrorless Mirror Descent: A More Natural Discretization of Riemannian Gradient Flow. CoRR abs/2004.01025 (2020) - Edward Moroshko, Suriya Gunasekar, Blake E. Woodworth, Jason D. Lee, Nathan Srebro, Daniel Soudry:
Implicit Bias in Deep Linear Classification: Initialization Scale vs Training Accuracy. CoRR abs/2007.06738 (2020) - Yiding Jiang, Pierre Foret, Scott Yak, Daniel M. Roy, Hossein Mobahi, Gintare Karolina Dziugaite, Samy Bengio, Suriya Gunasekar, Isabelle Guyon, Behnam Neyshabur:
NeurIPS 2020 Competition: Predicting Generalization in Deep Learning. CoRR abs/2012.07976 (2020) - 2019
- Mor Shpigel Nacson, Jason D. Lee, Suriya Gunasekar, Pedro Henrique Pamplona Savarese, Nathan Srebro, Daniel Soudry:
Convergence of Gradient Descent on Separable Data. AISTATS 2019: 3420-3428 - Mor Shpigel Nacson, Suriya Gunasekar, Jason D. Lee, Nathan Srebro, Daniel Soudry:
Lexicographic and Depth-Sensitive Margins in Homogeneous and Non-Homogeneous Deep Models. ICML 2019: 4683-4692 - Mor Shpigel Nacson, Suriya Gunasekar, Jason D. Lee, Nathan Srebro, Daniel Soudry:
Lexicographic and Depth-Sensitive Margins in Homogeneous and Non-Homogeneous Deep Models. CoRR abs/1905.07325 (2019) - Xiaoxia Wu, Edgar Dobriban, Tongzheng Ren, Shanshan Wu, Zhiyuan Li, Suriya Gunasekar, Rachel A. Ward, Qiang Liu:
Implicit Regularization of Normalization Methods. CoRR abs/1911.07956 (2019) - 2018
- Daniel Soudry, Elad Hoffer, Mor Shpigel Nacson, Suriya Gunasekar, Nathan Srebro:
The Implicit Bias of Gradient Descent on Separable Data. J. Mach. Learn. Res. 19: 70:1-70:57 (2018) - Suriya Gunasekar, Jason D. Lee, Daniel Soudry, Nathan Srebro:
Characterizing Implicit Bias in Terms of Optimization Geometry. ICML 2018: 1827-1836
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